marking the case_for_predictive_marketing___webinar_slides

Making the Case for Predictive

Your Speakers Today

Kerry Cunningham Sr. Research Director

@KerrySirius

Sean Zinsmeister Sr. Director, Product Marketing

@SZinsmeister

Nipul Chokshi VP Marketing

@nipulc

© 2016 SiriusDecisions. All Rights Reserved@KerrySirius 3

What is Predictive Analytics for B-to-B marketing?

Internal: MAP | SFA | Web

|CX

External: Intent |

DataInternal and External

StatisticsTo find patterns

**Statistics and advanced algorithms allow marketers to identify patterns that identify buyers that would be otherwise invisible; Machine Learning involves feedback loops embedded within statistical modeling processes to enable continuous model refinement

PredictionsDiscovered patterns

**Some vendors also add in additional services like data enrichment to enable more effective marketing and sales tactics

**Predictive Providers provide external data, which creates a much more complete view of who the prospects are and whether they are in the market for solutions

SiriusPerspective:


Grouping Waterfall Issues Addressed by Predictive

✓ Prospects in the TAM✓ AQLs for tele to call

effectively

✓ Inquiries hitting MAP✓ TGLs from tele

✓ AQLs from TQLs✓ C/W from pipeline✓ Calls to

conversations

Problem Example Solution

Too Many

Too Few

Conversion

Prioritize

Source

Engage

Demand Waterfall®

Total Addressable MarketInquires

AQLsTQLs

Closed/WonRetainedGrown

Knowing where to start with predictive begins by considering waterfall performance and understanding where performance needs to improve.

SiriusPerspective:


Grouping Waterfall Issues Addressed by PredictiveKnowing where to start with predictive begins by considering waterfall

performance and understanding where performance needs to improve.

Problem SolutionToo Many

Too Few

Conversion

Prioritize

Source

Engage

Demand Waterfall®

Total Addressable MarketInquires

AQLsTQLs

Closed/WonRetainedGrown

Predictive Analytics Use

Cases, Applications

Predictive


There’s A Predictive Application For That

Govern prospect outreach with findings from statistical analysis: best time to call by persona, region, etc.

Contact Engagement

Augment sales rep estimates for how likely a prospect is to buy, along with purchase timing and deal value

Opportunity Scoring

Determine existing customers’ propensity to buy additional products and identify attrition risk

Customer Scoring

Create more precise segmentation using an array of third-party data

Segmentation

Identify which buyers are more likely to prefer your brand and offerings using big data and analytics

Predictive Personas

Prioritize prospects for sales follow-up;

Replaces or augments existing point-based scoring systems

Prospect Prioritization

Detect buying journeys, deliver the next best communication using machine learning

Tactic Matching

Acquire new prospects that share traits and behaviors with known buyers or target prospects: look-alikes

Prospect Sourcing

Monitor shopping behaviors.

Source accounts that exhibit surges in shopping behaviors

Intent Monitoring


Predictive users must map the results of bottom-up modeling

processes to top-down derived beliefs

Top Down v. Bottom-Up Approaches

Top Down – We already know what constitutes a good prospect.

What sales says qualifies a prospect:

What the math says qualifies a prospect:

Implicit Explicit BANT

Intent data

Firmo Buy Signals

Tech –Inferred

Model variables

MAP Scoring/ Sales Qualification

Bottom Up – We let the data and statistical methods tell us how to identify the best prospects.

Tech

TOO MANY LEADS

Sales Prioritization

Sales Prioritization

Cost of Sales Team

$1.2M 30% $360,000

Bad Leads $$$$

Number of Sales Reps

20 Sales Reps $60,000 $1.2M

Average Monthly Cost per Rep $$$$

Sales Prioritization in Action

Kevin Gaither

Focused sales on highest value lead targets

Decreased time spent on bad leads by almost 20%

Established data-driven workflows with aggressive follow-up

Drove top-line results through effort reallocation

SVP of Sales

Fully Loaded Cost of the Inside Sales

Team

Headcount 19% $$$Sales Effort Saved by

Not Working Bad Leads

Monthly Cost Savings from Reduced Effort on Bad

Leads

Cost Savings

4x Conversion RateBy prioritizing leads based on data and following up more aggressively

3x Average Deal SizeBy spending more time on the right customers

Sales Prioritization in Action

Kevin Gaither

Focused sales on highest value lead targets

Decreased time spent on bad leads by almost 20%

Established data-driven workflows with aggressive follow-up

Drove top-line results through effort reallocation

SVP of Sales

Total Revenue by Lead Score

Before Infer (Day Zero) After Infer (Day 60)

Infer A-Leads

Infer B-Leads

Infer C-Leads

Infer D-Leads

+53%

+154%

+180%

+690%

+4xconversion

rate

+3xaverage deal size

+12xreturn on

investment

+19%sales effort

saved

Aligning Lead Effort with Impact

Lauren Licata

Reps call Infer A and B-Leads First

Email A Leads within 5 min and call within 1 hour vs. 8 hours it takes

Increased effort spent on A-Leads by 3x & decreased effort spent on D-Leads by 1.5x

Result: Increased sales by 30%

VP of Marketing

+30%increase in sales-

qualified leads

+30%lift in sales

~3xincrease in the effort

spent on A-Leads

1.5xdecrease in the

effort spent on D-Leads

2xlead to demo conversion

Using Fit & Behavior Buying Signals Together

Isaac Wyatt

Route best fit & engaged free-trials directly to sales

Find hidden segments of leads

Prioritize daily sales outreach

Interpate buying behavior

Director of Marketing Strategy & Operations

ALEXANDRE PAPILLAUD DIRECTOR, GLOBAL DEMAND CENTER, INTEL SECURITY

Lattice helps us filter out low probability leads before they reach sales. I love the ability to dive deep into the predictors of what makes a good lead…and our sales team loves Lattice because they know they are focused on the best opportunities.

Proprietary & Confidential

“20%Lower cost per

opportunity

Top 11% Convert at 6x Higher Rate

Data-driven Insights for Prioritizing Leads

Share of Servers Virtualized at Company

Public vs. Private Cloudat Company

Network-Based Storage at Company

Company is Undergoing Rapid Growth

Company is Using Amazon Web Services

10,000+ Business and Tech Attributes on 100M+ Entities

30%Greater velocity

We wanted sales to work the most enterprise-ready accounts. Lattice was able to surface accounts with high likelihood of conversion and accelerating them in the pipeline.”

“Shantel Shave Director, Demand Gen

Accelerating the Enterprise Business

TOO FEW LEADS

Security Software Provider: Creating Pipeline with Competitive Plays

26%Higher Win Rate

20%Higher call to win rates on list-based outbound

efforts

VP/GM of Distribution

We understand a good customer when it sees one, but with a small sales team, it would be impossible to visit millions of websites to find the ideal prospects. With Lattice, we can identify the right revenue opportunities.”

“Increasing Penetration into SMB

$1B+ Financial Payments Processor: Optimize list buys

30%Lower acquisition costs

Lattice customer since

2010

3xHigher conversions

Personalize Sales Interactions with 360-degree views of the customer

Top LinkedIn Post on Tuesday, 10/27/15

50%Lower cost per

opportunity

Direct Mail for High-Value, High Intent Targets

Direct Mail for High-Value, High Intent Targets

Identified high value targets

Determined buyer stage

Created custom data visualization

Added to direct mail campaign

Offer to meet and explain

Tangible package Automated follow-up Email & Phone call from rep

• How we created this? • Insights gained about

your network

Improving Marketing Efficiency

Kevin Bobowski

Route highest best leads to sales for immediate follow-up

Develop regular full-funnel pipeline forecasts

Continuously score marketing channels to test & invest

Optimized content syndication and list-buy programs

CMO

+50%marketing efficiency

+50%increase in monthly

pipeline creation

2.2xhigher converted A-Leads

than average

Campaign 1

Campaign 2

Leads Cost $ /Lead140

110

$5,000

$5,000

$35.71

$45.45

Campaign

Campaign 1 appears best under CPL metrics

A

B

C

Leads Opportunities Lead to Opp3,000

5,000

7,000

500

325

125

16.7%

6.5%

1.8%

Type of Lead

A-Leads worth almost 3x B-Leads

A

B

C

10

30

100

140 $5,000

Type of Lead

Campaign 1

Leads Cost $ / Lead Fcast Opps Forecast & / Opps

1.7

2.0

1.8

5.4$35.71 $926

A

B

C

35

30

45

110 $5,000

Type of Lead

Campaign 2

Leads Cost $ / Lead Fcast Opps Forecast & / Opps

5.8

2.0

0.8

8.6$45.45 $582

Campaign 2 wins on quality weighted cost

Adam von Reyn

Instant campaign feedback

Reduced cost-per-lead

Tests new marketing copy against D-Leads

Developed MQA for ABM strategy

Decreased 40% of total lead flow

VP of Growth Marketing

Scour your Marketing Systems

Real Results

5000Marketing-qualified

leads were unconverted in its

database, leading to a dramatic run-rate

increase

3xThe number of leads converted to closed

deals tripled

+150%Conversion rates

increased by 150%, from 0.8% to 2%

+76%Closed deals for new

solutions were boosted by 76%

POOR CONVERSION

• Ran a series of roadshows to drive pipeline for their Enterprise business

• Scored their database to identify high fit accounts who would receive targeted ads promoting the roadshows

• Identified high fit late stage buyers who would be invited directly by sales (in addition to receiving an ad)

• Enriched Marketo with account data so they could deliver hyper-personalized messages

Hyper-segmentation for ABM at Scale

40%

70%Greater ROI on ad spend

Increase in pipeline

35%

Higher engagement within target accounts

Ads Email SDR Calls

Every account gets scored and the next steps for engagement are initiated.

Lift curve changed to protect customer confidentiality

Score and Prioritize Targets

Lattice identifies the attributes that make a lead and account a good target for you

Orchestrate Multi-channel Outreach to Maximize Conversion

“A” Targets

Targeted Ads Personalized Email Invites

SDR Calls only for those in

market

“B” and ”C” Targets

Generic Email Invites

Orchestrate Multi-channel Outreach to Maximize Conversion

“A” Targets

Targeted Ads Personalized Email Invites

SDR Calls only for those in

market

“B” and ”C” Targets

Generic Email Invites

Personalize based on key attributes:

• Complementary tech • Amazon AWS • Google Cloud • Microsoft Azure

• Industry • Financial Services • High Tech • Telecom

Standard Ad Ad for companies using Amazon AWS

Ad for companies using Google Cloud

Example: Customer personalized their ads based on developer platforms they were using (e.g. Amazon AWS, Google Cloud,

etc).

Hyper-personalize Content and Messaging

Social Tables Challenge

Steady flow of 1,400 trial leads every month like

clockwork

Took on a paid content marketing strategy

Leads skyrocketed to 6,000 total Net New Leads per

month

#humblebrag

Month 1 Month 2 Month 3

At Social Tables all leads get assigned…

all 6,000…to 4 BDRs

Lead

M

anag

emen

tCollateral

AssignmentCapture/Nurture

General Analytics

>

>>

>>

>>

>

Hyper-Segmentation with Profiling

Ray Miller

Launched high-value outreach with personalized nurture

Identified 900+ high-potential prospects for sales

Hyper-segmented current and past trialers into ICPs

Prioritized A & B-Leads for accelerated sales follow-up

Senior Marketing Operations Manager

AT A GLANCE

+7%boosted overall revenue

+10%increased average deal size

+$500k/mogrew opportunity pipeline

+35%increased trial signups

+25%Expanded MQL volume

KEY CONSIDERATIONS TO GETTING STARTED

Sales & Marketing Alignment

Demand Gen compensation plan built on InferUses Infer to negotiate w/ partners and Lead providersLeverages Infer to overcome the Sales and Marketing divide to define MQL

Nick Ezzo VP Demand Gen

+23%Increase in Average Deal

Size

-53%Decline in poor quality

leads

Sales & Marketing Alignment

+200%Increase in incremental

revenue

+31%Lead to MQL improvement

Every company should use predictive analytics to gain clear customer parameters that the whole organization can agree on – now that we

have predictive scores, I’ll never go back.

Our Infer model makes all the difference when it comes to sales and marketing alignment.

Nick Ezzo, VP Demand Gen

DATA QUALITY MATTERS A Predictive Model is only as the good as the data that goes into it.

YOUR BUSINESS IS NOT ONE-SIZE-FITS-ALL And a One-Size-Fits-All modeling approach leads to bad results across your business.

OPERATIONALIZATION IS CRITICAL Marketing and Sales cannot execute without Full Transparency and Actionable Insights.

LACK OF ENTERPRISE SECURITY IS A NON-STARTER You are giving the vendor access to your CRM and MAP and your data needs to be protected.

Key Operational Considerations

THANK YOU!

Q&A

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Kerry Cunningham Sr. Research Director SiriusDecisions @KerrySirius

Sean Zinsmeister Sr. Director, Product Marketing Infer, Inc. @szinsmeister

Nipul Chokshi VP Marketing, Lattice Engines @nipulc

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